力量练习方法对跳跃能力影响的对比研究

传统的跳跃项目力量素质训练较多的采用＂负重半蹲杠铃＂的方法,这种方法属单关节的动作练习,只注重增强下肢力量,忽视了上下肢协调配合的作用。而＂抓举杠铃＂力量练习需要上肢和下肢的协调用力,正符合跳跃动作的结构特点。     

增价拍卖中投标者跳跃报价的收益效应研究

跳跃投标是增价拍卖一种普遍现象,而跳跃投标是否会带来投标方的期望收益的增加是一个值得关注的问题。通过运用博弈论方法,分别寻找单物品和多物品拍卖两种情形下的跳跃报价均衡,计算出跳跃报价均衡下的投标方期望收益,并将其结果与非跳跃报价情形进行比较,给出了投标方希望通过跳跃出价改善其期望收益的一般条件。     

跳高运动员心理自控能力的训练方法

通过对跳高运动员心理自控能力的训练经验进行分析,提出了几种心理自控能力的训练方法,并对在训练和比赛中的具体运用进行了论述.     

Change-point approach to data analytic wavelet thresholding

Previous proposals in data dependent wavelet threshold selection have used only the magnitudes of the wavelet coefficients in choosing a threshold for each level. Since a jump (or other unusual feature) in the underlying function results in several non-zero coefficients which are adjacent to each other, it is possible to use change-point approaches to take advantage of the information contained in the relative position of the coefficients as well as their magnitudes. The method introduced here represents an initial step in wavelet thresholding when coefficients are kept in the original order.     

水泥土粉喷桩强度试验与分析

水泥土搅拌法是就地将水泥和软土搅拌在一起的加固软土地基的一种方法，近年来得到广泛的应用，通过室内无侧限抗压强度试验和现场试验分析了水泥土的强度问题，供设计及施工人员参考。     

Total shift during the first passages of Markov-modulated Brownian motion with bilateral ph-type jumps: Formulas driven by the minimal solution matrix of a Riccati equation

This article describes our study of the total shift during the first passages (one-sided and two-sided exit times) of Markov-modulated Brownian motion with bilateral ph-type jumps, which is referred to as MMBM. The total shift is defined as the value of a so-called shift process at the first passage epochs of the MMBM. The shift process, introduced by Bean and O’Reilly, behaves like a continuous Markovian fluid process; that is, it increases or decreases linearly with slopes regulated by the underlying Markov process that determines the path of the MMBM. Hence, the notion of total shift, which includes the first passage times of the MMBM as special cases, is useful for describing various performance measures of systems modeled by the MMBM. In this article, we present formulas for the Laplace–Stieltjes transform matrices of the total shift during various first passages of the MMBM. In particular, a Riccati equation is derived so that a matrix associated with the Laplace–Stieltjes transform of the total shift during the first return time of the MMBM is its minimal non-negative solution matrix. With this solution matrix, the Laplace–Stieltjes transform matrices can be obtained without much additional work. Furthermore, it is shown that the Riccati equation satisfies the conditions for the Newton scheme to have quadratic convergence, which enables us to use algorithms with quadratic convergence, such as Newton’s method and the Stochastic Doubling Algorithm, to compute the presented matrix-driven formulas. For the analyses, we take an approach based on approximating the MMBM with a sequence of scaled Markov-modulated fluid flows with bilateral ph-type jumps, referred to as MMFF, that weakly converge to the MMBM. Another contribution of this article is that duality results are derived in relation to the MMBM, which is an extension of the duality theorems developed by Ahn and Ramaswami for an MMFF without a jump.     

基于时变跳跃次数的基准利率风险测算研究

各国央行包括美联储的利率调整和变动就是基准利率风险.基准利率的变化势必要导致金融资产定价的变动和风险溢价.本文通过自回归模型AR测算随时间变化的利率跳跃次数,确定基准利率跳跃的概率,利用伽马分布和正态分布分别测算基准利率跳跃的时间与幅度,根据利率跳跃的概率、时间和幅度确定基准利率跳跃风险溢价,建立基于时变跳跃次数的基准利率跳跃风险溢价测算模型,并利用中国上海证券交易所国债7天回购利率数据进行实证研究.本文创新与特色:1)通过自回归模型AR测算时变的利率跳跃次数,测算利率发生跳跃的概率,确定基准利率跳跃风险溢价,揭示跳跃次数的动态变化规律,反映历史利率跳跃行为对未来利率跳跃行为的影响,改变现有研究以常数跳跃次数测算利率跳跃概率、无法真实反映利率跳跃的频繁程度,导致利率跳跃概率及利率跳跃风险溢价测算不准的弊端.2)研究表明,现有研究的常数跳跃次数仅仅是本文跳跃次数测算模型在参数ρ、γ等于0时的特例.3)通过利率跳跃的概率、时间和幅度确定基准利率的跳跃风险溢价,解决基准利率跳跃风险补偿的测算问题.     

对提高我国跳高水平的新探索

根据目前我国跳高的现状和世界跳高运动的发展趋势，提出加强专项训练，形成以快速、灵活连贯为核心的技术风格，以及注意心理素质训练，提高大赛能力等观点     

参数组合的改变对铁饼飞行性能的影响

在铁饼风洞实验数据的基础上，结合实际投掷运动中容易出现的几种初始参数组合，对铁饼飞行空气动力学性能及对运动成绩的影响进行了系统的计算和比较分析，并从理论的层面上获得了符合运动实际的相关结论。     

An MCMC model search algorithm for regression problems

In this paper, we improve upon the Carlin and Chib Markov chain Monte Carlo algorithm that searches in model and parameter spaces. Our proposed algorithm attempts non-uniformly chosen ‘local’ moves in the model space and avoids some pitfalls of other existing algorithms. In a series of examples with linear and logistic regression, we report evidence that our proposed algorithm performs better than the existing algorithms.